{"id":"W1994107552","doi":"10.1115/1.3290768","title":"3D Simulation of Manufacturing Defects for Tolerance Analysis","year":2010,"lang":"en","type":"article","venue":"Journal of Computing and Information Science in Engineering","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Machining; Quality (philosophy); Context (archaeology); Reliability engineering; Process (computing); Manufacturing engineering; Engineering; Product (mathematics); Computer science; Engineering drawing; Interval (graph theory); Tolerance analysis; Industrial engineering; Mechanical engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004055334,0.0005550179,0.0005179467,0.0006864667,0.0002593822,0.000852001,0.0007324587,0.001393804,0.00422377],"category_scores_gemma":[0.0014613,0.0003680692,0.0007250506,0.0005223729,0.0005816715,0.000373571,0.0005708868,0.0004958615,0.0003464839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005711956,"about_ca_system_score_gemma":0.0005128938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007870248,"about_ca_topic_score_gemma":0.003628028,"domain_scores_codex":[0.9997661,0.00006601983,0.00001335038,0.00002370444,0.0001039877,0.0000267885],"domain_scores_gemma":[0.9989999,0.000633723,0.0001056,0.0001054016,0.0001231975,0.00003216829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001571789,0.00001151634,0.000249904,0.00001000518,0.000004279904,0.00002331783,0.00001925438,0.9969472,0.0007636551,0.0006214567,0.00006090038,0.001272797],"study_design_scores_gemma":[0.000003297799,0.000008525539,0.00009088134,0.000001714319,0.000001495543,0.000004910745,0.000004187229,0.9991898,0.0003745852,0.0001448334,0.0001728,0.000002913549],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4942169,0.0002861482,0.4802763,0.0003346768,0.0001285927,0.0001351068,0.001201729,0.001904912,0.02151557],"genre_scores_gemma":[0.9604483,0.0001209064,0.03729583,0.0000377333,0.000009846032,0.00009795443,0.0002492553,0.00008746464,0.001652669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007870248,"threshold_uncertainty_score":0.0156489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004933490483531811,"score_gpt":0.2279249661803203,"score_spread":0.2229914756967885,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}